alt Hacker NewsAn elephant in the room is that if you have too much data to process without AI, you have too many results to check for correctness when they come out of the AI.
This has been true since before LLMs, but now so many more people and use cases are enabled so much more easily. People are undisciplined and quick to take short term gains and handwave the correctness.
It is less of a problem if the output is explicitly marked as AI-generated and unverified, so people can treat it as a rough first draft. But mix AI output with well-vetted human-reviewed data, and you've basically made your entire data set worthless.